AI Agent Index
ByHeather MacAvelia·Independently reviewed·Published Aug 18, 2026·Updated Sep 14, 2026
Independently verified against live vendor data on Sep 2, 2026.
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screenpipe

4.0/ 5

by Negentropy Labs, Inc.

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Local-first screen and audio memory for AI agents: screenpipe captures your desktop activity, keeps it on your machine, and serves it to MCP clients through a local server with two documented tools.

How we scored it

Autonomy

4/5

Integrations

5/5

Pricing clarity

4/5

Evidence

3/5

Setup

5/5

The facts

screenpipe is a local-first memory layer: a desktop agent that records what you see and hear on your own machine, stores it locally, and makes it searchable by the AI tools you already use. Negentropy Labs, Inc., trading as screenpipe, ships it for macOS, Windows and Linux, and describes the product as source-available rather than open source. Capture works through the operating system rather than through integrations. The app reads on-screen text primarily via accessibility APIs with OCR as a fallback, transcribes audio locally, and writes everything to a local store on your own disk. The pricing page puts the cost of that at roughly 30 GB per month of continuous recording, while the About page FAQ still says 5 to 10 GB, and retention is configurable either way. On macOS the app needs both screen recording and accessibility access granted in System Settings before it captures anything. For retrieval, screenpipe runs a local MCP server, installed with npx -y screenpipe-mcp, and exposes exactly two documented tools: search-content, which queries recorded screen text, audio transcriptions and input events with content-type, time-range and pagination parameters, and export-video. The vendor documents one-click installation into Claude Desktop from the app's own settings panel, plus manual stdio configuration for Claude Code, OpenAI Codex, Cursor and Warp, and generic instructions for other editors. An optional HTTP transport covers clients that cannot speak stdio. Under all of it sits a local REST API on port 3030, which is also what the MCP server talks to, so a pipe or a script can read the same history without going through an AI client at all. Pipes are the automation half, and the docs call them scheduled AI agents. Each is a markdown file carrying a prompt and a schedule: every 30 minutes, every 2 hours, daily, a cron expression, or manual, which is the default until one is set. A running pipe can query the capture database, write files, call external APIs and send notifications. The documented connections cover Slack, Notion, Google Calendar, Obsidian, HubSpot, Salesforce, Zoom, PostHog and Sentry. The vendor's own examples are tracking time in Toggl from app usage, writing daily summaries to Obsidian, and sending a Slack message after 30 minutes on a site. Scheduled workflows are a priced line on the plan comparison, limited on Free and unlimited from Basic upward. Several of the vendor's published recipes are deliberately review-gated instead, drafting a follow-up queue or CRM fields for a person to approve. Pricing is published on the page the /pricing path resolves to, and there are four plans. Free is $0 on one device. Basic is $25 per month, or $21 per month billed annually at $250 per year. Business is $50 per seat per month, or $500 per seat per year, with a seven-day free trial. Enterprise is priced through a contact form, and it is the only tier with SSO and MDM controls. Students, researchers and faculty get 50% off the first month. Each plan includes AI credits that reset monthly, at 10 on Free, 150 on Basic and 400 on Business, with Max and Ultra add-ons at 800 and 1,600 credits for single-user Business capacity. A user's own provider key can be used instead where supported. The About page still lists an older ladder of $25, $50 and $150 per month and its structured data still carries a $25 offer, so the two vendor surfaces differ. Currency is USD on both. On privacy the architecture and the legal terms address different things. Data stays on the device by default, cloud model calls send only the query, and Ollama can be used for fully local inference. The terms state that customer content, output and personal information are not used to train models without separate written agreement. The same section then has the user consent, by using the service, to the creation and use of Deidentified Data and Analytics Data including to improve and train the vendor's own models. The public repository carries 21.6k GitHub stars, and its license is not an OSI license: personal, non-commercial and evaluation use can be free while commercial use requires a paid license under the Screenpipe Commercial License. Current state Q3 2026: the local MCP server documents two tools, search-content and export-video. The /pricing path resolves to a plan page listing Free, Basic, Business and Enterprise, while the About page carries an older three-tier ladder. GitHub reports the repository license as Other rather than an OSI license, and the Terms of Service, last updated 2 September 2026, name Negentropy Labs, Inc. as the operator.

Pricing

freemium · $21/mo annual

View pricing ↗

Segment

both

Setup

moderate

Verified

Sep 2, 2026

Transparency

Mostly Public

Contract

Monthly or Annual

Data training

Not Trained

Human in loop

Optional

Capabilities

screen-capturecontext-memorylocal-firstmcp-serverbyok

Pros & Limitations

Editorial assessment

Pros

  • Local-first by architecture rather than by policy: capture, storage and search all sit on your own machine, cloud model calls send only the query, and Ollama support means the whole loop can run without a single cloud call.
  • A first-party MCP server rather than a claim: npx -y screenpipe-mcp exposes search-content and export-video over a local REST API on port 3030. It installs with one click into Claude Desktop from the app's own settings panel, with documented stdio setups for Claude Code, OpenAI Codex, Cursor and Warp.
  • A free plan on one device and two published paid rates: Basic at $21 per month billed annually, and Business at $500 per seat per year with a seven-day trial. Getting running is a desktop install on macOS, Windows or Linux against a documented five-minute quickstart.

Limitations

  • The trust portal, under the name Mediar, Inc., lists SOC 2 Type 2, ISO 27001, GDPR and HIPAA as compliant. The vendor's security page describes ISO 27001 as in progress, and GDPR, HIPAA and CCPA as internal programs rather than certifications. Independent review volume is two Product Hunt reviews and a G2 profile with no reviews yet.
  • Section 4 of the terms has the user consent, by using the service, to the vendor creating Deidentified Data and Analytics Data from usage and using it to improve and train its models. Customer content, output and personal information are excluded without separate written agreement.
  • The public source is under the Screenpipe Commercial License rather than an OSI license: personal, non-commercial and evaluation use can be free, and commercial use requires a paid license. Continuous recording uses roughly 30 GB of local disk per month.

Technical Details

Deployment
desktopcliapi
Model architectureBring your own model (cloud LLM APIs, or fully local inference via Ollama)
Avg setup time< 15 minutes (download the desktop app, grant screen recording and accessibility permissions, connect one MCP client). The vendor quickstart claims five minutes.
Autonomous rateCapture is continuous and unattended once permissions are granted. Pipes are scheduled agents: a prompt plus a schedule of every 30 minutes, every 2 hours, daily or a cron expression, with manual the default until one is set. A running pipe can write files, call external APIs and send notifications through connections including Slack, Notion, HubSpot and Salesforce. The MCP surface is separate and read-oriented: two tools, search-content and export-video. No autonomous task-completion rate is published on any first-party surface.
Integrations
SlackNotionGoogle CalendarObsidianTogglHubSpotClaude DesktopClaude CodeOpenAI CodexCursorWarpOllama
Security
SOC 2 Type IIGDPRCCPA

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Rating

4.0/ 5

Editorial score

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Recognition

MCP Server VerifiedListed 2026
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